Global summary

Identifying changes in the reproduction number, rate of spread, and doubling time during the course of the COVID-19 outbreak whilst accounting for potential biases due to delays in case reporting both nationally and subnationally. These results are impacted by changes in testing effort, increases and decreases in testing effort will increase and decrease reproduction number estimates respectively (see Methods or our paper for further explanation).

Using data available up to the: 2020-07-03

Note that it takes time for infection to cause symptoms, to get tested for SARS-CoV-2 infection, for a positive test to return and ultimately to enter the case data presented here. In other words, today’s case data are only informative of new infections about two weeks ago. This is reflected in the plots below, which are by date of infection.

Expected daily confirmed cases by country


Figure 1: The results of the latest reproduction number estimates (based on estimated confirmed cases with a date of infection on the 2020-06-22) can be summarised by whether confirmed cases are likely increasing or decreasing. This represents the strength of the evidence that the reproduction number in each region is greater than or less than 1, respectively (see the methods for details). Countries with fewer than 60 confirmed cases reported on a single day are not included in the analysis (light grey) as there is not enough data to reliably estimate the reproduction number.

Summary of latest reproduction number and confirmed case count estimates by date of infection


Figure 1: Confirmed cases with date of infection on the 2020-06-22 and the time-varying estimate of the effective reproduction number (light bar = 90% credible interval; dark bar = the 50% credible interval.). Regions are ordered by the number of expected daily confirmed cases and shaded based on the expected change in daily confirmedcases. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control and a single case required for elimination.

Reproduction numbers over time in the six regions expected to have the most new confirmed cases


Figure 2: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-06-22 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Confirmed cases and their estimated date of infection in the six regions expected to have the most new confirmed cases


Figure 3: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-06-22 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Reproduction numbers over time in all regions


Figure 4: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-06-22 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Confirmed cases and their estimated date of infection in all regions

Figure 5: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-06-22 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Latest estimates (as of the 2020-06-22)

Table 1: Latest estimates (as of the 2020-06-22) of the number of confirmed cases by date of infection, the effective reproduction number, and the doubling time (when negative this corresponds to the halving time) in each region. The mean and 90% credible interval is shown.
Country New confirmed cases by infection date Expected change in daily cases Effective reproduction no. Doubling/halving time (days)
Afghanistan 310 (277 – 349) Decreasing 0.9 (0.8 – 1) -21 (-88 – -12)
Albania 68 (51 – 83) Unsure 1.1 (0.9 – 1.2) 44 (11 – -20)
Algeria 294 (253 – 336) Increasing 1.3 (1.2 – 1.4) 9 (6.7 – 14)
Andorra 5 (0 – 13) Unsure 1.4 (0 – 2.9) 3.3 (1 – -2.7)
Argentina 2703 (2492 – 2920) Increasing 1.2 (1.1 – 1.2) 17 (14 – 22)
Armenia 577 (527 – 622) Unsure 1 (0.9 – 1.1) 250 (35 – -48)
Australia 58 (45 – 73) Increasing 1.4 (1.1 – 1.6) 8.3 (4.8 – 28)
Austria 63 (46 – 76) Increasing 1.2 (1 – 1.5) 13 (6.6 – 3200)
Azerbaijan 572 (520 – 637) Increasing 1.1 (1 – 1.2) 26 (16 – 70)
Bahrain 578 (514 – 627) Increasing 1.1 (1 – 1.1) 36 (19 – 220)
Bangladesh 3940 (3645 – 4215) Increasing 1.1 (1 – 1.1) 39 (28 – 68)
Belarus 383 (342 – 419) Decreasing 0.9 (0.8 – 0.9) -18 (-36 – -12)
Belgium 85 (64 – 103) Unsure 1.1 (0.9 – 1.2) 42 (11 – -23)
Benin 53 (37 – 67) Unsure 1 (0.8 – 1.3) 75 (11 – -16)
Bolivia 1016 (936 – 1099) Increasing 1.1 (1 – 1.1) 56 (28 – 11000)
Bosnia and Herzegovina 125 (102 – 144) Increasing 1.2 (1.1 – 1.4) 13 (7.5 – 41)
Brazil 38757 (36841 – 40972) Increasing 1.1 (1.1 – 1.1) 32 (27 – 39)
Bulgaria 129 (108 – 148) Likely increasing 1.1 (1 – 1.2) 25 (11 – -91)
Cameroon 58 (38 – 77) Decreasing 0.5 (0.4 – 0.6) -3.9 (-5.3 – -3.1)
Canada 298 (265 – 334) Likely decreasing 1 (0.9 – 1) -64 (59 – -21)
Cape Verde 41 (30 – 54) Likely increasing 1.2 (0.9 – 1.4) 17 (6.6 – -29)
Central African Republic 102 (82 – 118) Unsure 1.1 (0.9 – 1.2) 49 (13 – -28)
Chad 5 (0 – 11) Likely increasing 1.7 (0.5 – 2.9) 4.8 (1.6 – -4.6)
Chile 4094 (3853 – 4316) Decreasing 0.8 (0.8 – 0.9) -12 (-23 – -7.9)
China 23 (14 – 31) Unsure 0.9 (0.6 – 1.1) -23 (15 – -6.6)
Colombia 3661 (3416 – 3934) Increasing 1.1 (1.1 – 1.2) 21 (17 – 27)
Congo 37 (25 – 45) Unsure 1.1 (0.8 – 1.3) 150 (10 – -12)
Costa Rica 174 (153 – 198) Increasing 1.2 (1.1 – 1.4) 12 (7.9 – 29)
Cote dIvoire 247 (218 – 274) Likely decreasing 1 (0.9 – 1) -36 (120 – -16)
Croatia 60 (44 – 72) Increasing 1.3 (1 – 1.6) 9.4 (5.2 – 49)
Cuba 7 (1 – 11) Unsure 1.1 (0.4 – 1.8) 30 (3.1 – -4)
Czechia 187 (159 – 216) Increasing 1.3 (1.2 – 1.5) 8.7 (6.1 – 16)
Democratic Republic of the Congo 135 (113 – 155) Unsure 1 (0.9 – 1.1) -63 (34 – -16)
Denmark 31 (21 – 41) Unsure 0.9 (0.7 – 1.1) -32 (17 – -8.2)
Djibouti 14 (7 – 20) Unsure 1 (0.6 – 1.4) 33 (5.3 – -7.7)
Dominican Republic 716 (643 – 785) Increasing 1.1 (1 – 1.2) 34 (20 – 140)
Ecuador 869 (764 – 960) Increasing 1.2 (1.1 – 1.3) 13 (9.8 – 18)
Egypt 1567 (1449 – 1706) Increasing 1.1 (1 – 1.1) 53 (29 – 420)
El Salvador 224 (196 – 251) Increasing 1.2 (1 – 1.3) 19 (11 – 78)
Equatorial Guinea 102 (79 – 122) Increasing 1.8 (1.4 – 2.3) 3.7 (2.7 – 5.7)
Estonia 5 (0 – 10) Unsure 1.6 (0.2 – 2.8) 4.8 (1.5 – -3.8)
Ethiopia 164 (140 – 185) Unsure 1 (0.9 – 1.1) -100 (32 – -20)
Finland 12 (5 – 18) Unsure 1.2 (0.7 – 1.7) 13 (3.8 – -9.7)
France 623 (541 – 701) Increasing 1.2 (1.1 – 1.3) 19 (12 – 48)
Gabon 80 (63 – 95) Decreasing 0.9 (0.7 – 1) -25 (53 – -10)
Germany 485 (442 – 535) Unsure 1 (0.9 – 1) -44 (300 – -21)
Ghana 460 (411 – 505) Increasing 1.1 (1.1 – 1.2) 21 (13 – 49)
Greece 19 (11 – 27) Unsure 1.1 (0.7 – 1.4) 49 (6.4 – -8.7)
Guatemala 612 (539 – 680) Increasing 1.1 (1 – 1.2) 27 (16 – 81)
Guinea 40 (27 – 52) Likely decreasing 0.9 (0.7 – 1) -15 (51 – -6.6)
Guinea Bissau 16 (9 – 23) Unsure 1.2 (0.8 – 1.7) 13 (4.1 – -11)
Haiti 85 (68 – 101) Likely decreasing 0.9 (0.8 – 1) -32 (37 – -11)
Honduras 833 (758 – 918) Increasing 1.2 (1.1 – 1.2) 20 (14 – 35)
Hungary 9 (3 – 15) Unsure 1.2 (0.7 – 1.8) 11 (3.2 – -7.4)
Iceland 5 (1 – 10) Likely increasing 1.5 (0.6 – 2.5) 6.7 (2.1 – -5.4)
India 19481 (18190 – 20775) Increasing 1.1 (1.1 – 1.2) 21 (19 – 24)
Indonesia 1292 (1188 – 1414) Increasing 1.1 (1 – 1.2) 28 (19 – 57)
Iran 2647 (2460 – 2829) Increasing 1 (1 – 1.1) 60 (35 – 220)
Iraq 2194 (2029 – 2348) Increasing 1.1 (1.1 – 1.2) 26 (19 – 41)
Ireland 12 (6 – 18) Unsure 1.2 (0.7 – 1.6) 14 (3.9 – -9.5)
Israel 629 (547 – 716) Increasing 1.3 (1.2 – 1.4) 8.6 (7 – 11)
Italy 221 (192 – 247) Unsure 1 (0.9 – 1.1) -840 (27 – -25)
Japan 112 (88 – 132) Increasing 1.3 (1.1 – 1.4) 11 (6.6 – 27)
Kazakhstan 3383 (2745 – 4124) Increasing 1.8 (1.6 – 2.1) 4 (3.5 – 4.7)
Kenya 212 (186 – 239) Increasing 1.1 (1 – 1.2) 26 (13 – -650)
Kosovo 93 (74 – 108) Likely increasing 1.1 (0.9 – 1.2) 32 (11 – -34)
Kuwait 754 (698 – 820) Increasing 1.1 (1 – 1.2) 27 (17 – 66)
Kyrgyzstan 283 (251 – 313) Increasing 1.2 (1.1 – 1.3) 14 (9.4 – 30)
Latvia 4 (0 – 8) Unsure 1.7 (0.4 – 3) 4.7 (1.5 – -3.9)
Lebanon 24 (13 – 32) Unsure 1 (0.8 – 1.3) 340 (8.4 – -8.8)
Libya 33 (22 – 43) Likely increasing 1.1 (0.9 – 1.4) 23 (6.9 – -18)
Lithuania 7 (0 – 13) Unsure 1.3 (0.4 – 2.2) 11 (2.3 – -4)
Luxembourg 31 (18 – 41) Increasing 1.5 (1.1 – 1.9) 6.6 (3.6 – 36)
Madagascar 75 (59 – 90) Likely increasing 1.1 (0.9 – 1.3) 32 (10 – -30)
Malawi 64 (50 – 77) Likely increasing 1.1 (1 – 1.4) 25 (9 – -30)
Malaysia 13 (3 – 20) Unsure 1 (0.6 – 1.5) 100 (4.8 – -5.2)
Maldives 20 (11 – 28) Unsure 1 (0.7 – 1.3) 530 (7.3 – -7.7)
Mali 32 (19 – 43) Likely increasing 1.2 (0.9 – 1.5) 12 (5.1 – -41)
Mauritania 166 (145 – 191) Unsure 1 (0.9 – 1.1) 360 (21 – -25)
Mexico 5248 (4934 – 5557) Increasing 1 (1 – 1.1) 100 (55 – 600)
Moldova 275 (241 – 305) Likely decreasing 0.9 (0.9 – 1) -37 (160 – -17)
Mongolia 7 (0 – 15) Unsure 1.6 (0.4 – 2.6) 6.6 (1.9 – -4.3)
Morocco 272 (237 – 300) Likely increasing 1.1 (0.9 – 1.2) 47 (17 – -66)
Namibia 30 (20 – 39) Increasing 1.6 (1.1 – 2) 5.6 (3.3 – 18)
Nepal 561 (507 – 609) Increasing 1.1 (1 – 1.2) 23 (14 – 58)
Netherlands 79 (61 – 94) Likely decreasing 0.9 (0.7 – 1.1) -43 (25 – -12)
New Zealand 6 (0 – 12) Likely increasing 1.7 (0.4 – 2.7) 6.1 (1.9 – -4.7)
Niger 8 (2 – 14) Unsure 1.1 (0.6 – 1.7) 50 (3.8 – -4.6)
Nigeria 663 (589 – 719) Increasing 1.1 (1 – 1.1) 45 (22 – -1200)
North Macedonia 143 (123 – 164) Unsure 1 (0.9 – 1.1) 420 (20 – -22)
Norway 18 (10 – 26) Unsure 1.1 (0.7 – 1.4) 46 (6.2 – -8.9)
Oman 1153 (1068 – 1236) Likely increasing 1.1 (1 – 1.1) 43 (24 – 250)
Pakistan 3810 (3550 – 4104) Decreasing 0.9 (0.9 – 1) -38 (-160 – -22)
Palestine 230 (201 – 257) Increasing 1.3 (1.1 – 1.5) 10 (7.1 – 18)
Panama 932 (849 – 1020) Increasing 1.1 (1 – 1.2) 30 (19 – 72)
Paraguay 105 (84 – 126) Increasing 1.3 (1.1 – 1.6) 8.2 (5.1 – 22)
Peru 3608 (3419 – 3826) Likely increasing 1 (1 – 1.1) 57 (36 – 140)
Philippines 913 (823 – 999) Increasing 1.1 (1.1 – 1.2) 22 (15 – 37)
Poland 294 (255 – 327) Unsure 1 (0.9 – 1.1) -210 (33 – -26)
Portugal 353 (310 – 386) Likely increasing 1 (1 – 1.1) 81 (24 – -58)
Puerto Rico 110 (88 – 127) Unsure 1 (0.9 – 1.1) 800 (18 – -19)
Qatar 957 (888 – 1033) Likely decreasing 1 (0.9 – 1) -120 (100 – -39)
Romania 356 (316 – 396) Increasing 1.1 (1 – 1.2) 32 (16 – 70000)
Russia 7168 (6749 – 7610) Unsure 1 (1 – 1) -370 (150 – -84)
Rwanda 37 (24 – 48) Likely increasing 1.2 (0.9 – 1.4) 20 (6.7 – -18)
Saudi Arabia 3980 (3680 – 4276) Increasing 1.1 (1 – 1.1) 74 (32 – -280)
Senegal 112 (94 – 128) Unsure 1 (0.9 – 1.1) 250 (18 – -21)
Serbia 233 (196 – 268) Increasing 1.4 (1.2 – 1.5) 8.2 (6 – 13)
Sierra Leone 21 (13 – 29) Unsure 1.1 (0.7 – 1.4) 27 (5.8 – -10)
Singapore 224 (188 – 256) Unsure 1 (0.9 – 1.2) 43 (16 – -62)
Slovakia 12 (6 – 18) Likely increasing 1.2 (0.8 – 1.7) 14 (4.1 – -9.8)
Somalia 15 (6 – 21) Likely decreasing 0.8 (0.5 – 1.1) -14 (16 – -4.9)
South Africa 6937 (6387 – 7466) Increasing 1.2 (1.1 – 1.3) 14 (12 – 17)
South Korea 51 (35 – 63) Unsure 1.1 (0.9 – 1.3) 37 (9.1 – -18)
South Sudan 18 (10 – 26) Unsure 0.9 (0.6 – 1.2) -54 (8.9 – -6.6)
Spain 372 (329 – 409) Likely increasing 1.1 (1 – 1.1) 49 (19 – -95)
Sri Lanka 11 (4 – 18) Unsure 1.1 (0.6 – 1.5) 47 (5.1 – -6.7)
Sudan 90 (75 – 107) Decreasing 0.8 (0.7 – 1) -13 (-54 – -7.3)
Suriname 30 (18 – 40) Likely increasing 1.3 (1 – 1.6) 9.4 (4.5 – -79)
Sweden 1172 (1080 – 1260) Likely increasing 1 (1 – 1.1) 32 (18 – 160)
Switzerland 79 (58 – 97) Increasing 1.4 (1.2 – 1.7) 6.5 (4.4 – 13)
Tajikistan 56 (42 – 69) Unsure 1 (0.8 – 1.2) -140 (15 – -12)
Thailand 5 (0 – 9) Unsure 1.4 (0.6 – 2.3) 7.6 (2.3 – -5.7)
Tunisia 6 (0 – 11) Unsure 1.2 (0.3 – 2) 35 (2.7 – -3.2)
Turkey 1417 (1314 – 1523) Increasing 1.1 (1 – 1.1) 45 (26 – 160)
Uganda 16 (7 – 24) Unsure 1.2 (0.8 – 1.6) 17 (4.6 – -11)
Ukraine 862 (800 – 924) Likely increasing 1 (1 – 1.1) 110 (35 – -100)
United Arab Emirates 440 (388 – 483) Likely increasing 1.1 (1 – 1.1) 39 (19 – -580)
United Kingdom 954 (871 – 1025) Likely decreasing 0.9 (0.9 – 1) -49 (-960 – -25)
United Republic of Tanzania 10 (4 – 15) Decreasing 0.7 (0.4 – 1) -8.5 (28 – -3.7)
United States of America 44599 (41696 – 48053) Increasing 1.2 (1.1 – 1.2) 16 (15 – 18)
Uzbekistan 273 (238 – 298) Increasing 1.1 (1 – 1.2) 19 (11 – 61)
Venezuela 238 (216 – 266) Increasing 1.2 (1.1 – 1.3) 18 (11 – 62)
Western Sahara 63 (46 – 77) Increasing 1.8 (1.3 – 2.2) 4.1 (2.8 – 7.1)
Yemen 25 (15 – 33) Unsure 1 (0.7 – 1.3) 28 (6.8 – -13)
Zambia 23 (13 – 31) Likely increasing 1.2 (0.9 – 1.6) 10 (4.4 – -32)
Zimbabwe 12 (4 – 18) Unsure 1 (0.6 – 1.3) -30 (7.6 – -4.9)